Recent research progress of paper-based supercapacitors based on cellulose
Bibliographic record
Abstract
With the rapid development of science and technology, paper-based functional materials have become the core of the field of new materials. Recently, they have received extensive attention in the field of energy storage due to their advantages of rich and adjustable porous network structure, good flexibility. As an important energy storage device, paper-based supercapacitors have important application prospects in many fields, and have also received extensive attention from researchers in recent years. At present, researchers have modified and regulated paper-based materials by different means such as structural design and material composition to enhance their electrochemical storage capacity. The development of paper-based supercapacitors provides an important direction for the development of green and sustainable energy. Therefore, it is of great significance to summarize the relevant work of paper-based supercapacitors for their rapid development and application. In this review, the recent research progress of paper-based supercapacitors based on cellulose was summarized in terms of various cellulose-based composites, preparation skills and electrochemical performance. Finally, some opinions on the problems in the development of this field and the future development trend were proposed. It is hoped that this review can provide valuable references and ideas for the rapid development of paper-based energy storage devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".